Prescribed Performance Function Based Sliding Mode Control of Opposing Pneumatic Artificial Muscles to Enhance Safety

The field of rehabilitation robotics has seen a significant increase in the utilization of Pneumatic Artificial Muscle (PAM)-based systems in recent years. These systems have demonstrated great potential in assisting and enhancing human movements and motor functions. However, as with any system that involves human interaction, safety is of the utmost importance. It is essential to ensure that the tracking error is kept within a safe range to prevent harm to people and equipment. This research proposes a control strategy that combines the exponential reaching law with a prescribed performance function to enhance safety in PAM-based rehabilitation robots. The prescribed performance function is designed to regulate the tracking error within predetermined limits during short and long-term operations, thereby mitigating large oscillations that may damage mechanical structures and patients. The experimental results indicate that the proposed controller demonstrated superior tracking accuracy and safety performance compared to traditional control methods. It is hoped that the findings of this study will contribute to developing safe and effective rehabilitation systems for patients in need

Response Surface Designs Robust against Nuisance Factors

This paper discusses an algorithmic approach to constructing trend-free and orthogonally-blocked response surface designs. The constructed designs have the main effects, 2-factor interactions and second-order effects being orthogonal or near-orthogonal to the nuisance factors such as the time-trend or the blocking factors. The paper also provides a catalogue of (near-) trend-free Box–Behnkens designs and orthogonally blocked Box–Behnkens designs arranged in rows and columns

An Updated Loop-Mediated Isothermal Amplification Method for Rapid Diagnosis of H5N1 Avian Influenza Viruses

We designed a new set of primers for reverse transcriptase loop-mediated isothermal amplification (RTLAMP) to specifically amplify the HA gene of avian influenza viruses subtype H5N1. By testing nine H5N1 virus strains and 41 clinical samples collected in Northern Vietnam, we found that the new primers showed higher sensitivity and specificity than the previously published RT-LAMP primers and were comparable to the RT-PCR method currently recommended by WHO. These results suggest that our RT-LAMP assay may be a better choice as a diagnostic tool for current H5N1 influenza virus infection

Designs for Screening Experiments with Quantitative Factors

Most screening experiments in chemometrics and science are quantitative, i.e. continuous factors. These factors should be 3-level and the designs for these experiments should also be 3-level. However, popular designs for screening experiments are still Plackett-Burman designs (PBDs) and 2-level fractional factorial designs (FFDs) such as resolution III and resolution IV FFDs. This chapter introduces the conference matrices as an alternative to PBDs and resolution III FFDs and definitive screening designs, a conference matrix-based class of designs, as an alternative to resolution IV FFDs. A table of conference matrices of up to order 32 and examples are also provided for illustration

Catalytic Dye Oxidation over CeO2 Nanoparticles Supported on Regenerated Cellulose Membrane

A novel regenerated cellulose (RC) membrane containing cerium oxide (CeO2) nanoparticles is described in detail. In this work, CeO2 nanoparticles with high surface area and mesoporosity were prepared by a modified template-assisted precipitation method. Successful synthesis was achieved using cerium nitrate as a precursor, adjusting the final pH solution to around 11 by ammonium hydroxide and ethylene diamine, and annealing at 550 °C for 3 hours under a protective gas flow. This resulted in a surface area of 55.55 m².g–1 for the nanoparticles. The regenerated cellulose membrane containing CeO2 particles was synthesized by the novel and environmentally friendly method. The catalyst CeO2 and cellulose/CeO2 membrane were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), Electron paramagnetic resonance (EPR), and Brunauer-Emmett-Teller (BET) measurements. The g-value of 2.276 has confirmed the presence of the surface superoxide species of CeO2 nanoparticles in EPR. The photocatalytic activity of the catalyst and the membrane containing the catalyst was evaluated through the degradation of methylene blue under visible light irradiation by UV-VIS measurements. The cellulose/CeO2 membrane degraded 80% of the methylene blue solution in 120 minutes, showing a better photocatalytic activity than the CeO2 catalyst, which degraded approximately 62% in the same period. It has been proven that the RC membrane is not only a good transparent supporting material but also a good adsorption for high-performance of CeO2 catalyst. Copyright © 2022 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Prospects for Food Fermentation in South-East Asia, Topics From the Tropical Fermentation and Biotechnology Network at the End of the AsiFood Erasmus+Project

Fermentation has been used for centuries to produce food in South-East Asia and some foods of this region are famous in the whole world. However, in the twenty first century, issues like food safety and quality must be addressed in a world changing from local business to globalization. In Western countries, the answer to these questions has been made through hygienisation, generalization of the use of starters, specialization of agriculture and use of long-distance transportation. This may have resulted in a loss in the taste and typicity of the products, in an extensive use of antibiotics and other chemicals and eventually, in a loss in the confidence of consumers to the products. The challenges awaiting fermentation in South-East Asia are thus to improve safety and quality in a sustainable system producing tasty and typical fermented products and valorising by-products. At the end of the “AsiFood Erasmus+ project” (www.asifood.org), the goal of this paper is to present and discuss these challenges as addressed by the Tropical Fermentation Network, a group of researchers from universities, research centers and companies in Asia and Europe. This paper presents current actions and prospects on hygienic, environmental, sensorial and nutritional qualities of traditional fermented food including screening of functional bacteria and starters, food safety strategies, research for new antimicrobial compounds, development of more sustainable fermentations and valorisation of by-products. A specificity of this network is also the multidisciplinary approach dealing with microbiology, food, chemical, sensorial, and genetic analyses, biotechnology, food supply chain, consumers and ethnology

Spatiotemporal evolution of SARS-CoV-2 Alpha and Delta variants during large nationwide outbreak of COVID-19, Vietnam, 2021

We analyzed 1,303 SARS-CoV-2 whole-genome sequences from Vietnam, and found the Alpha and Delta variants were responsible for a large nationwide outbreak of COVID-19 in 2021. The Delta variant was confined to the AY.57 lineage and caused >1.7 million infections and >32,000 deaths. Viral transmission was strongly affected by nonpharmaceutical interventions

Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery